egutierrez
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- .claude/CLAUDE.md - .claude/commands/subagentes.md - .claude/rules/INDEX.md - .mcp.json - bash/functions/cybersecurity/analyze_dns.md - bash/functions/cybersecurity/audit_http_headers.md - bash/functions/cybersecurity/audit_ssh_config.md - bash/functions/cybersecurity/check_firewall.md - bash/functions/cybersecurity/detect_suspicious_users.md - bash/functions/cybersecurity/encrypt_file.md - ... Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
869 B
869 B
name, kind, lang, domain, version, purity, signature, description, tags, uses_functions, uses_types, returns, returns_optional, error_type, imports, params, output, tested, tests, test_file_path, file_path
| name | kind | lang | domain | version | purity | signature | description | tags | uses_functions | uses_types | returns | returns_optional | error_type | imports | params | output | tested | tests | test_file_path | file_path | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| standardize | function | py | datascience | 1.0.0 | pure | def standardize(data: list) -> list | Estandarizacion Z-score: transforma los datos a media=0 y desviacion=1. |
|
false |
|
|
lista de misma longitud con datos transformados a media=0 y desviacion estandar=1 (z-scores) | false | python/functions/datascience/datascience.py |
Ejemplo
standardize([10, 20, 30])
# [-1.2247..., 0.0, 1.2247...]
Notas
Si la desviacion estandar es cero, retorna lista de ceros. Usa desviacion poblacional (N, no N-1).